Describing Pulmonary Nodules Using 3D Clustering by Amera Al-Funjan, Farid Meziane, Rob Aspin

“…This paper combines algorithms to cluster and define nodule’s features in 3D visualization. …”
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Zero Watermarking Algorithm for Hyperspectral Remote Sensing Images Considering Spectral and Spatial Features by Bingbing Yang, Haowen Yan, Liming Zhang, Qingbo Yan, Zhaoyang Hou, Xiaolong Wang, Xinyu Xu

“…Most existing zero-watermarking algorithms for remote sensing images are designed for panchromatic or multispectral data. …”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

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Unsupervised SAR Image Change Detection Based on Curvelet Fusion and Local Patch Similarity Information Clustering by Yuhao Huang, Zhihui Xin, Guisheng Liao, Penghui Huang, Guangyu Hou, Rui Zou

“…Then the proposed local patch similarity information clustering algorithm is used to classify the image pixels to output the final change map. …”
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Optimization algorithm of CT image edge segmentation using improved convolution neural network. by Xiaojuan Wang, Yuntao Wei

“…Firstly, the pattern clustering algorithm is applied to cluster the pixels with relationship in the CT sequence image space to extract the edge information of the real CT image; secondly, Euclidean distance is used to calculate similarity and measure similarity, according to the measurement results, convolution neural network (CNN) hierarchical optimization is carried out to improve the convergence ability of CNN; finally, the pixel classification of CT sequence images is carried out, and the edge segmentation of CT sequence images is optimized according to the classification results. …”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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Sparse Feature-Weighted Double Laplacian Rank Constraint Non-Negative Matrix Factorization for Image Clustering by Hu Ma, Ziping Ma, Huirong Li, Jingyu Wang

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Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm by He Chuan, Qiu Dishan, Liu Jin

“…Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. …”
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Digital image representation by atomic functions: features for computer vision and machine learning by Viktor Makarichev, Vladimir Lukin, Sergii Kryvenko, Iryna Brysina

“…The focus of this work is to assess whether DAT is suitable for ML and CV applications, particularly in the context of image clustering. We evaluated the performance of the well-known k-means clustering algorithm when applied to DAT images. …”
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Continuum topological derivative - A novel application tool for segmentation of CT and MRI images by Viswanath Muthukrishnan, Sandeep Jaipurkar, Nedumaran Damodaran

“…Following this, segmentation of the region of interest was performed using the CTD technique, with comparisons made against Discrete Topological Derivatives (DTD), k-mean clustering and Adaptive Threshold methods. Evaluation of the proposed CTD algorithm's effectiveness in segmentation involved calculating performance metrics such as Jaccard and dice indices to assess spatial overlap of segmented images. …”
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A New Texture Aware—Seed Demand Enhanced Simple Non-Iterative Clustering (ESNIC) Segmentation Algorithm for Efficient Land Use and Land Cover Mapping on Remote Sensing Images by Rohini Selvaraj, D. Geraldine Bessie Amali

“…This paper proposes a texture-aware and seed-demanding Enhanced Simple Non-Iterative Clustering (ESNIC) segmentation algorithm and Boundary-Specific Two-Level (BSTL) classification approach that reduces misclassification rates due to similar spectral signatures and minimizes computational redundancy. …”
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Microc alcification Segmentation Using Modified U-net Segmentation Network from Mammogram Images by Md Shamim Hossain

“…The suspicious regions are detected using fuzzy C-means clustering algorithm and divided them into negative and positive patches. …”
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Multi-Dimensional Lithology Identification Method Based on Microresistivity Image Logging by LIU Juan, MIN Xuanlin, QI Zhongli, YI Jun, LAI Fuqiang, ZHOU Wei

“…First, Filtersim algorithm is employed to fill the blank strip of electrical imaging, and K-means++ clustering in pixel-wise is performed on the filled data to mark the weak noise such as cracks and karst caves, so as to avoid introducing noise into color clustering. …”
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Data Clustering Using by Chaotic SSPCO Algorithm by OICC Press Authors

“…Data clustering is a popular analysis tool for data statistics in several fields, including includes pattern recognition, data mining, machine learning, image analysis and bioinformatics, in which the information to be analyzed can be of any distribution in size and shape. …”
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A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise. by Wei Zhang, Xiaolong Zhang, Juanjuan Zhao, Yan Qiang, Qi Tian, Xiaoxian Tang

“…Hexagonal clustering and morphological optimized sequential linear iterative clustering (HMSLIC) for sequence image oversegmentation is then proposed to obtain superpixel blocks. …”
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Image Recognition Technology in Texture Identification of Marine Sediment Sonar Image by Chao Sun, Li Wang, Nan Wang, Shaohua Jin

“…At the same time, considering the scale complexity, diversity, multisources, and small sample characteristics of the marine sediment sonar image texture, the transfer learning is introduced into the image recognition, and the K-means clustering algorithm is used to reset the prior frame parameters to improve the speed and accuracy of image recognition. …”
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A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus by Csaba Dávid, Kristóf Giber, Katalin Kerti-Szigeti, Mihály Köllő, Zoltan Nusser, Laszlo Acsady

“…Here, we propose a spatial autocorrelation method based on Local Moran’s I coefficient to differentiate signal, background, and noise in any type of image. The method, originally described for geoinformatics, does not require a predefined intensity threshold or teaching algorithm for image segmentation and allows quantitative comparison of samples obtained in different conditions. …”
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Image-Text Joint Learning for Social Images with Spatial Relation Model by Jiangfan Feng, Xuejun Fu, Yao Zhou, Yuling Zhu, Xiaobo Luo

“…This article forms the perspective of the spatial relationship to exploring the joint learning of social images. Precisely, the model consists of three parts: (a) a module for deep semantic understanding of images based on residual network (ResNet); (b) a deep semantic analysis module of text beyond traditional word bag methods; (c) a joint reasoning module from which the text weights obtained using image features on self-attention and a novel tree-based clustering algorithm. …”
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Improving and simulating urban landscape image recognition using combination optimization and fuzzy K-means algorithm by Lihua Yang, Yuhui Zheng

“…It has proven highly effective in detecting and classifying mixed-use urban zones, delivering greater accuracy in recognition tasks than traditional clustering algorithms.…”
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Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation by Wu LX, Ding N, Ji YD, Zhang YC, Li MJ, Shen JC, Hu HT, Jin L, Yin SN

“…In this review, we aim to briefly summarize the widely used cluster analysis algorithms in subregion segmentation and the application of habitat analysis in tumor imaging. …”
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